The present application generally relates to managing a business organization, a business process, an industrial process or machinery, and other similar entities. More particularly, the present application relates to building of associated functions of statistical or causal models for monitoring and managing the performance of such entities by using metric data that monitor the operations of the entities.
As data storage costs decrease and automated systems increase, business organizations collect and store increasing numbers of business metrics (e.g., revenue, size of sales force, etc.) from which the business organization would like to extract an insight (e.g., an overall performance measurement or metric of the sales force). The metrics are typically collected and aggregated across multiple dimensions, e.g., geography, product line(s), business unit(s), etc. to provide different views to business users having different roles in the organization. For managing the overall performance of the business organization, business analysts have had increasing difficulty in identifying a “right” set of metrics to report, monitor, and manage. To identify the right set of metrics, the business analysts have found it useful to find out answers to the following exemplary questions: (1) At what level of a hierarchy (e.g., a tree data structure representing the taxonomy related to the organization or business process in question) are there most meaningful patterns among the metrics? (2) What are the relationships between the metrics? (3) Are relationships among the metrics similar for different categories within one or more levels of the hierarchy? (4) What may happen to the value of a certain metric of interest for a certain node in the hierarchy, if the organization managed to change the value of other metric(s)? An example of the fourth question in the context of business performance metric management may be “What may happen to total sales in USA if the organization increases sales resources only in the eastern region of USA?”